spannerlib-python 0.1.1

A Python wrapper for the Go spannerlib. This is an internal library that can make breaking changes without prior notice.

SPANNERLIB-PYTHON: A High-Performance Python Wrapper for the Go Spanner Client Shared lib

NOTICE: This is an internal library that can make breaking changes without prior notice.

Introduction

The spannerlib-python wrapper provides a high-performance, idiomatic Python interface for Google Cloud Spanner by wrapping the official Go Client Shared library.

The Go library is compiled into a C-shared library, and this project calls it directly from Python, aiming to combine Go's performance with Python's ease of use.

Installation

To install the library, use pip:

pip install spannerlib-python

Usage

Here is a simple example of how to use the library to execute a SQL query.

1. Import the library

from google.cloud.spannerlib import Pool
from google.cloud.spanner_v1 import ExecuteSqlRequest

2. Create a connection pool

Initialize the pool with your database connection string.

connection_string = "projects/<your-project>/instances/<your-instance>/databases/<your-database>"
pool = Pool.create_pool(connection_string)

3. Create a connection

conn = pool.create_connection()

4. Execute a query

Use ExecuteSqlRequest to specify your SQL query.

sql = "SELECT 'Hello, World!' as greeting"
request = ExecuteSqlRequest(sql=sql)

# Execute the query
rows = conn.execute(request)

# Iterate over the results
while True:
    row = rows.next()
    if row is None:
        break
    # row is a google.protobuf.struct_pb2.ListValue
    print(row.values[0].string_value)

# Close the rows object when done
rows.close()

5. Cleanup

Always close the connection and pool to release resources.

conn.close()
pool.close()

Using Context Managers

You can also use the with statement to automatically manage resources (close connections and pools).

from google.cloud.spannerlib import Pool
from google.cloud.spanner_v1 import ExecuteSqlRequest

connection_string = "projects/<your-project>/instances/<your-instance>/databases/<your-database>"

# Pool and Connection are context managers
with Pool.create_pool(connection_string) as pool:
    with pool.create_connection() as conn:
        sql = "SELECT 'Hello, World!' as greeting"
        request = ExecuteSqlRequest(sql=sql)
        
        # Rows/Results are also context managers
        with conn.execute(request) as rows:
            for row in iter(rows.next, None):
                print(row.values[0].string_value)
# Resources are automatically closed here